AI Solutions Engineer

Your role and responsibilities
In this role, you will develop and deploy end-to-end AI and machine learning solutions that address complex business challenges across Operations, Sales, and Service functions. This role combines technical expertise in ML/AI with business acumen to translate customer needs into scalable, production-ready AI solutions. The engineer works closely with data engineers, product managers, and business stakeholders to architect, build, test, and optimize AI models while ensuring solution quality, governance, and measurable business impact.

The work model for this role is: #LI-Hybrid
You will be mainly accountable for:

• Designing, developing, and deploying machine learning models and AI solutions to solve business challenges in operations, maintenance, forecasting, and process optimization.
• Architecting end-to-end ML workflows, including data preparation, feature engineering, model development, validation, and production deployment.
• Conducting exploratory data analysis, feasibility assessments, and proof-of-concept (POC) initiatives to evaluate business value and technical viability.
• Collaborating with data engineers and cross-functional teams to build scalable data pipelines and ensure high-quality training datasets.
• Applying ML engineering and MLOps best practices, including model versioning, CI/CD, containerization, monitoring, governance, and documentation.
• Monitoring model performance in production, address model drift, and implement retraining strategies to maintain accuracy and business relevance.
• Communicating AI/ML insights to technical and non-technical stakeholders, contribute to engineering standards, and drive adoption of emerging AI technologies and best practices.

Qualifications for the role

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a related technical discipline; Master's degree in Machine Learning, Data Science, Artificial Intelligence, or a related field is an advantage.
• Around 5 years of hands-on experience in Machine Learning, Data Science, or AI solution development within a commercial or enterprise environment.
• Demonstrated success in designing, developing, and deploying machine learning models into production environments at scale.
• Strong programming skills in Python, with practical experience using ML frameworks and libraries such as Scikit-learn, TensorFlow, and PyTorch.
• Experience working with cloud-based machine learning platforms, including AWS SageMaker, Azure Machine Learning, or Google Vertex AI.
• Solid understanding of MLOps, model lifecycle management, and deployment pipelines, with exposure to business-driven AI use cases such as predictive maintenance, forecasting, optimization, or intelligent automation.

What’s in it for you?

We want you to bring your full self to work—your ideas, your energy, your ambition. You’ll have the tools and freedom to grow your skills, shape your path, and take on challenges that matter. Here, your work creates impact you can see and feel, every day. 

More about us

ABB's Service Division partners with our customers to improve the availability, reliability, predictability and sustainability of electrical products and installations. The Division’s extensive service portfolio offers product care, modernization, and advisory services to improve performance, extend equipment lifetime and deliver new levels of operational and sustainable efficiency. We help customers keep resources in use for as long as possible, extracting the maximum value from them, and then recovering and regenerating products and materials at the end of their useful life.